@article{941,
  author = {Romain Mavudila Kongo, Lhousaine MASMOUDI, Mohammed CHERKAOUI, Ahmed ROUKHE},
  title = {Dual-Tree Wavelet Transform for Medical Image Watermarking},
  journal = {Journal of E-Technology},
  year = {2012},
  volume = {3},
  number = {3},
  doi = {},
  url = {http://www.dline.info/jet/fulltext/v3n3/4.pdf},
  abstract = {Wavelet techniques can be successfully applied in various image processing methods, namely in image denoising ,segmentation, classification, watermarking and others. Given the earlier works of watermarking images based on DT-CWT, our approach shown that it is possible to generalize their conclusions and to show some results in the medical watermarking images. It has been demonstrated in the literature that the Complex Wavelet Transform (DT-CWT), has significant advantages over classic Discrete Wavelet Transform (DWT), for certain image processing problems. The DT-CWT is a form of Discrete Wavelet Transform which generates complex coefficients by using a dual tree of wavelet filters to obtain their real and imaginary parts. The main part of the paper is devoted to exploit the exceptional quality of DT-CWT combined with Bivariate Shrinkage with Local Variance Estimation at the extracted step of the watermark in the blind watermarking of medical images. The results of simulation showed that DT-CWT gave better quality of watermarked images and preserved a integrity of image after extracting watermark. We suggested that the findings obtained by this study will help to uncover in medical watermarking images and seemed to reaffirm the findings of previous researches in robustness and traceability and transparency preservation.},
}